The integration of the Global Positioning System (GPS) and the Inertial Navigation System (INS) has been implemented for several years due the complementary features of both systems. GPS technology can provide positioning solutions with long-term stability using the line-of-sight signals from receiver to the GPS satellites. However, GPS suffers from the interrupt and degradation caused by all kinds of disturbances of the satellites signals. On the contrary, INS is a self-contained system that can provide a continuous navigation solution (position, velocity and attitude) from a given initial status, but has long-term unbounded drift errors. Therefore, GPS and INS are often combined (especially when using low-cost systems) as an integrated navigation system with other sensors. Due to the complementary characteristics of GPS and INS, such an integrated system requires less accurate INS for general navigation applications, and thus, the limitations due to price, availability and access restrictions of higher grade (navigation or high-end tactical) Inertial Measurement Units (IMUs) are minimized.
Essentially, inertial sensors are making use of the inertia of the proof mass in the sensors. The larger the mass, the better the performance. This fact constitutes the reason why typical Micro-Electro-Mechanical Systems (MEMS) inertial sensors have relatively poor quality compared to traditional sensors. Furthermore, due to the low-cost and bulk productivity of the MEMS sensors, the manufacturers are not able to calibrate each individual sensor. In addition, manufacturers also do not give comprehensive specifications of the sensors in terms of navigation performance which is a major demand for any user. Therefore, the evaluation of MEMS sensors and the corresponding MEMS IMUs in terms of navigation performance is extremely important to the user of such systems. There are several conventional methods to make such an evaluation.
One such method is lab testing which can provide sensor parameters such as noise density, bias instability, Scale Factor (SF) instability, non-orthogonality, non-linearity, g-sensitivity of gyroscopes, and temperature sensitivities (bias and SF). However this method cannot directly predict the navigation performance of the inertial MEMS. The navigation performance can be predicted theoretically by analyzing the error propagation in the INS mechanization and the steady state of the Kalman Filter (KF). In this case, only the sensors errors that are modeled by the KF can be considered (e.g. white noise, bias instability and SF instability). The navigation errors induced by other errors cannot be typically investigated. Therefore the results of such analyses are poor representation of the actual navigation cases.
Another conventional method includes using an INS simulator to simulate the true angular rate and specific force (i.e. the ideal outputs of the gyros and accelerometers according to the motions assigned by users). The errors of the inertial sensors are simulated (according to the specifications or the lab testing) and then added to the true signals to get simulated IMU signals. These signals are processed by the GPS/INS navigation algorithm to investigate the navigation performance. This method is more realistic than lab testing of the sensors. However, both the body motion and the sensor errors are simulated, and these parameters typically differ from the actual values. Moreover, some sensor errors are difficult to model and simulate, such as non-linearity and temperature sensitivities. Furthermore, GPS signals need to be simulated as well.
A third conventional method is field testing. GPS/INS field testing is the only way to evaluate the performance of MEMS IMUs in a realistic situation, especially when GPS signals are temporarily blocked. The advantage of field testing method is that the vehicle motion, sensor errors and GPS signals are all real. The disadvantage of field testing is that the method is frequently time consuming and costly to perform. It is even more expensive and time-consuming to make comprehensive tests that cover a variety of trajectories and GPS signal conditions. Furthermore, a higher grade (navigation or high-end tactical) IMU is necessary to investigate the errors of the tested MEMS IMU, which will further increase the cost and complexity of the test.